dataset:
  name: mnli
  path: datasets/TextClassification/mnli

plm:
  model_name: roberta
  model_path: ../../plm_cache/roberta-large
  optimize:
    freeze_para: True
    lr: 0.0003
    weight_decay: 0.01
    scheduler:
      type: 
      num_warmup_steps: 500

dataloader:
  max_seq_length: 128

train:
  num_epochs: 30
  batch_size: 30
  gradient_accumulation_steps: 1

test:
  batch_size: 10

valid:
  batch_size: 10


template: mixed_template
verbalizer: manual_verbalizer


mixed_template:
  choice: 1
  file_path: scripts/TextClassification/mnli/mixed_template.txt
  optimize:
    lr: 0.003
    weight_decay: 0.0
    scheduler:
      num_warmup_steps: 0

manual_verbalizer:
  choice: 0
  file_path: scripts/TextClassification/mnli/multiwords_verbalizer.jsonl
  
environment:
  num_gpus: 1
  cuda_visible_devices:
    - 0
  local_rank: 0

learning_setting: full


task: classification
classification:
  parent_config: task
  metric:  # the first one will be the main  to determine checkpoint.
    - accuracy  # whether the higher metric value is better.
  loss_function: cross_entropy ## the loss function for classification